A weighted mean filter with spatial-bias elimination for impulse noise removal

In this paper, we propose Unbiased Weighted Mean Filter (UWMF) for removing high-density impulse noise. Asymmetric distribution of corrupted pixels in the filtering window creates a spatial-bias towards the center of uncorrupted pixels. UWMF eliminates this bias by recalibrating the contribution factor (weight) of each uncorrupted pixel in such a way that the center shifts back to the center of the filtering window. The restoration process involves three sequential operations while convolving a filtering window over a contaminated image. Noise is detected, weights are recalibrated and the new intensity value is replaced by weighted mean using the recalibrated weights. Compared to the state-of-the-art impulse noise removal methods, UWMF provides superior performance, without requiring a fine-tuning for its parameters, in terms of both objective measurements and subjective assessments. (C) 2015 Elsevier Inc. All rights reserved.